Impact of social distancing measures for preventing coronavirus disease 2019 [COVID-19]: A systematic review and meta-analysis protocol

  1. Krishna Regmi
  2. Cho Mar Lwin

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Introduction

Social distancing measures (SDMs) protect public health from the outbreak of coronavirus disease 2019 (COVID-19). However, the impact of SDMs has been inconsistent and unclear. This study aims to assess the effects of SDMs (e.g. isolation, quarantine) for reducing the transmission of COVID-19.

Methods and analysis

We will conduct a systematic review meta-analysis research of both randomised controlled trials and non-randomised controlled trials. We will search MEDLINE, EMBASE, Allied & Complementary Medicine, COVID-19 Research and WHO database on COVID-19 for primary studies assessing the effects of SDMs (e.g. isolation, quarantine) for reducing the transmission of COVID-19, and will be reported in accordance with PRISMA statement. The PRISMA-P checklist will be used while preparing this protocol. We will use Joanna Briggs Institute guidelines (JBI Critical Appraisal Checklists) to assess the methodological qualities and synthesised performing thematic analysis. Two reviewers will independently screen the papers and extracted data. If sufficient data are available, the random-effects model for meta-analysis will be performed to measure the effect size of SDMs or the strengths of relationships. To assess the heterogeneity of effects, I 2 together with the observed effects (Q-value, with degrees of freedom) will be used to provide the true effects in the analysis.

Ethics and dissemination

Ethics approval and consent will not be required for this systematic review of the literature as it does not involve human participation. We will be able to disseminate the study findings using the following strategies: we will be publishing at least one paper in peer-reviewed journals, and an abstract will be presented at suitable national/international conferences or workshops. We will also share important information with public health authorities as well as with the World Health Organization. In addition, we may post the submitted manuscript under review to bioRxiv, medRxiv, or other relevant pre-print servers.

Strengths and limitations of this study

  • To our knowledge, this study will be the first systematic review to examine the impact of social distancing measures to reduce transmission of COVID-19.

  • This study will offer highest level of evidence for informed decisions, drawing a broader framework.

  • This protocol reduces the possibility of duplication, provides transparency to the methods and procedures that will be used, minimise potential biases and allows peer-review.

  • This research is not externally funded, and therefore time and resource will be constrained.

  • If included studies will be variable in sample size, quality and population, which may open to bias, and the heterogeneity of data will preclude a meaningful meta-analysis to measure the impact of specific SDMs

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.06.13.20130294: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: Patient and public involvement: As this is a protocol for a systematic review and meta-analysis, neither patients nor public participation will be directly involved, and ethics approval and consent will not be required either. Dissemination: We will be able to disseminate the study findings using the following strategies: we will be publishing at least one paper in peer-reviewed journals, and an abstract will be presented at suitable national/international conferences or workshops.
    Randomizationnot detected.
    Blinding” Generally, the bias table provides the type of bias (e.g., selective reporting of outcomes, random sequence generation, allocation of concealment, blinding of participants, personnel and assessors, incomplete outcome data and other potential threats to validity) in each study.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line AuthenticationAuthentication: We will also ask subject experts/information specialists from authors’ Universities to verify the research strategy, ensuring its comprehensiveness.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    34 The Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) checklist has been used in the preparation of this protocol.35 Criteria for considering studies for review: Inclusion criteria Exclusion criteria Search strategy to identify relevant studies: Five major databases will be searched: MEDLINE, EMBASE, Allied & Complementary Medicine, COVID-19 Research and WHO database on COVID-19.
    MEDLINE
    suggested: (MEDLINE, RRID:SCR_002185)
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    Primary search terms are SDMs (all synonyms) and COVID-19 (all synonyms) using ‘Textword searching’ – searching for a word or phrase appearing anywhere in the document, where the document is the citation (article title, journal name, author), not the full text of an article, and ‘Thesaurus (MeSH, EMTREE) searching’, employing Boolean operators and truncations.
    MeSH
    suggested: (MeSH, RRID:SCR_004750)
    The ‘Related Articles’ including the best match and most recent features in PubMed will be consulted.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Selection of studies: The citations identified through the searches will be imported into Mendeley Reference Manager (https://www.mendeley.com/).
    https://www.mendeley.com/
    suggested: (Mendeley Data, RRID:SCR_002750)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The potential limitations of this study would be that if the retrieved studies would be variable in sample size, quality and population, which may open to bias, and the heterogeneity of data precludes a meaningful meta-analysis to measure the impact of specific SDMs for COVID-19, therefore the findings might warrant generalisation. Second, methodologies might be poorly reported (mostly due to preprints - postings in MedRxiv), lacking comprehensive strategies for sampling and procedures, and lacking detail in data gathering and analysis. Wolkewitz and Puljak53 warned that: “there are many methodological challenges related to producing, gathering, analysing, reporting and publishing data in condensed timelines required during a pandemic.” Third, searching “social distancing” in different databases might be challenging mainly due to rapidly-growing COVID-19 studies in PubMed and other search interfaces, which are not visible in the major search databases (PubMed, EMBASE) due to i) indexing, and ii) often bibliographic databases failed to capture preprint and unpublished studies including registered clinical trials,54,55 and the majority are commentaries, news, perspectives or opinions.53 Finally, this research is not externally funded, and therefore time and resource will be constrained. Nevertheless, this study will add to the literature on highlighting the major enablers and barriers of SDM in controlling COVID-19 in public health policy and interventions: i) given the fact th...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.06.13.20130294v1 on medRxiv